a) Temporal expression dynamic of Brn3a dependent RGC type specification genes. (Muzyka et al., JCN 2018) Brn3a is a member of the Brn3/Pou4f transcription factor family, which contains key regulators of RGC postmitotic specification. In particular, Brn3a ablation results in the loss of RGCs with small, thick and dense dendritic arbors (midget-like RGCs), and morphological changes in other RGC subpopulations. To identify downstream molecular mechanisms underlying Brn3a effects on RGC numbers and morphology, our group recently performed a RNA deep sequencing screen for Brn3a transcriptional targets in mouse RGCs and identified 180 candidate transcripts. We focused on a subset of 28 candidate genes encoding potential cell type determinant proteins. We validated and further defined their retinal expression profile at five postnatal developmental time points between birth and adult stage, using in situ hybridization (ISH), RT-PCR and fluorescent immunodetection (IIF). We found that a majority of candidate genes were enriched in the ganglion cell layer during early stages of postnatal development, but dynamically change their expression profile. We also document transcript-specific expression differences for two example candidates (Pnkd and Clcc-1), using RT-PCR and ISH. Brn3a dependency could be confirmed by ISH and IIF for a fraction of our candidates. Amongst our candidate Brn3a target genes, a majority demonstrated ganglion cell layer specificity, however only around two thirds showed Brn3a dependency. Some were previously implicated in RGC type specification, while others have known physiological functions in RGCs. Only three genes were found to be consistently regulated by Brn3a throughout postnatal retina development. We have now selected a few of the more promising leads and pursue their RGC type distribution and involvement in RGC type specification. b) Combinatorial expression of the Neurotrophin receptor Ret and Brn3 transcription factors in retinal neurons (Parmhans et al 2018). Our gene expression profiling of Brn3 positive RGC populations suggested a complicated combinatorial code involving further transcriptional regulators and adhesion molecules involved in RGC type specification. One dimension of this complexity is the neurotrophic support and feedback distinct neuronal subtypes might obtain based on their developmental niche and synaptic partners. We had previously established that Brn3s also participate in a combinatorial fashion in the specification of somatosensory neurons of the Dorsal Root Ganglion and Trigeminal Ganglion. Cell type specification of these projection sensory neurons is regulated by an interplay between transcriptional regulation and neurotrophic signaling, as exemplified by the work of our collaborator, Dr. Wenqin Luo, in U. Penn. We therefore were curios to explore the expression overlap between the Ret neurotrophin receptor and the Brn3 transcription factors in RGCs, and found that distinct types of RGCs are differentially expressing Ret and and Brn3s in combination. We are now taking advantage of this knowledge to define the genetic interactions between ret and Brn3s in these RGC types. c) Visual Behavior Tests: We have imported the commercial version of our behavior system, produced by Phenosys GMBH, and integrated it in the visual Core of the NEI, where it can be used under the supervision of Dr. Hahua Qian, by all researchers of the NEI and NIH. We are now implementing several new behavior tests looking at visually cued freezing and fleeing reactions, and have uncovered surprising new phenotypes in some of our genetic backgrounds. A manuscript is in preparation. d) Multichannel electrophysiology for the analysis of Retinal Ganglion Cell Function (Ghahari et al 2018) In this past year we have continued our development of a machine learning algorithm for the unsupervised detection and classification of RGC recordings from ex vivo retinas stimulated with a variety of visual stimuli. We had published a short report on a skeleton version of the algorithm, and have another manuscript for the full version under review. We now have finalized the spike sorting algorhithm, and published its application to a subset of our data on wild type retinas challenged with full field visual stimuli. We have also implemented a novel GPU-based spikesorting approach, developed by Marius Pachitariu at UCL, and are applying it to our datasets. We have evaluated CMOS-based multielectrode array systems and identified a workable pipeline for our needs. e) RGC-32 involvement in Th17 responses during experimentally induced autoimmune reactions (Tatomir et al 2018) While in Dr. Horea Russ lab at University of Maryland Medical System, I had cloned and characterized RGC-32, a vertebrate specific gene upregulated in proliferating tissues, regenerative context, and tumors. Injured tissues react by inflammatory responses that attempt to clear the noxious influence, but at the same time repair the damage. Somatic cells can be affected in a variety of ways by these signals. One type of adaptive response is the induction of stress response genes, assumption of less mature tissue phenotypes, or even reactivation of cell cycle. Dr. Rus and I conducted a screen for genes induced by complement system challenge in primary oligodendrocyte cell cultures. We further characterized one of the identified genes, RGC-32, and showed that it interacts with cell cycle regulators, and can positively or negatively affect cell cycle activation in different contexts. More recently, I have collaborated with Dr. Rus to generate a knock-out for RGC-32, and members of his group discovered that RGC-32 is highly enriched in T lymphocytes and can play a role in their differentiation towards the Th17 fate. This in turn could affect the progression of experimentally induced auto-immune reactions (experimental autoimmune Encephalomyelitis EAE, a murine model for multiple sclerosis). Thus RGC-32 could be a potential regulator of tissue repair or regeneration, in particular in the context of inflammatory processes. During this last year we dug deeper into the mechanisms by which RGC-32 modulates the inflammatory response during EAE, and looked at interactions with the TGFbetta pathway, gliosis and scar tissue deposition. We are in the process of validating an RGC-32 conditional animal, in order to selectively ablate the gene from different cell populations involved in the autoimmune response in EAE, and further dissect its mechanistic role.